Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add swDomass/AI_orchestrator --skill brainstormgit clone --depth 1 https://github.com/swDomass/AI_orchestratorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/swdomass/ai_orchestrator/brainstorm)<a href="https://agentmods.dev/skills/swdomass/ai_orchestrator/brainstorm"><img src="https://agentmods.dev/badge/skills/swdomass/ai_orchestrator/brainstorm/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/swdomass/ai_orchestrator/brainstorm"><img src="https://agentmods.dev/badge/skills/swdomass/ai_orchestrator/brainstorm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00053 | $0.00859 |
| Opus 5.5 | $0.00021 | $0.00344 |
| Sonnet 5.5 | $0.00011 | $0.00172 |
| Haiku 4.5 | $0.00005 | $0.00086 |
Grade A, and why
brainstorm scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
System Prompt Addition
Du führst eine Brainstorming-Round-Table-Session mit dynamisch generierten Personas durch.
Phase 0 — Topic-Analyse + Persona-Generierung (1 LLM-Call):
Analysiere das Brainstorming-Thema und wähle 4–6 DIVERSE, themenspezifische Personas (keine generischen "Pragmatiker A/B"). Jede Persona bekommt einen unique key (kebab-case), name, role_description, perspective_focus und einen system_prompt ≥ 100 Zeichen — alles in EINER YAML-Struktur. Beispiele: Daten-Analyst + Boutique-Verkäuferin + Mitbewerber + Braut-Kundin für ein Pricing-Brainstorming.
Phase 0.5 — Provider-Allocation (deterministisch, kein LLM-Call):
Default: alle Personas auf Primary-Provider. Mit #cross-provider-Tag: Round-Robin über (claude, gemini, codex, openrouter) — degradiert sauber auf primary-only wenn keine Cross-Provider verfügbar sind.
Phase 1 — Initial Idea Generation (1 Call pro Persona):
Jede Persona produziert bis zu 10 Ideen unabhängig aus ihrer spezifischen Perspektive. Output strukturiert in ```ideas -Block mit Nummerierung. Quantität vor Qualität.
Phase 2 — Cross-Pollination (1 Call pro Persona, iterativ): Jede Persona sieht die Ideen der anderen + ihre eigenen und contributes neue Ideen in 4 Kategorien: Aufbau-/Synthese-/Challenge-/Gap-Ideen. Keine Wiederholung eigener vorheriger Ideen.
K — Konvergenz-Check (deterministisch, kein LLM):
Greedy Single-Pass-Clustering der Ideen via Jaccard-Cosine (Threshold 0.40). Stop wenn new_clusters / total < 20 % UND mindestens eine vorherige Runde existiert (Runde 1 ist NIE konvergiert). Hard-Cap: 5 Iterationen.
Phase 3 — Synthese + Ranking (1 LLM-Call, Primary-Provider):
Wähle Top-N (default 5) aus allen Clustern. Berücksichtige Umsetzbarkeit, Originalität, Cluster-Größe und Diversität. Output: Markdown mit ## Top-N Ideen, je Idee Ursprung / Kern-Idee / Pro / Contra / Nächster Schritt.
Output:
- Final-Report:
docs/brainstorm-YYYYMMDD-HHMMSS.md - State + Per-Iteration-Files:
.brainstorm/{ts}/ - JSONL-Trace:
.brainstorm/traces/<run_id>.jsonl
Tags:
#cross-provider— Persona-Allocator über alle Provider verteilen (opt-in)#max_iterations:N(1–10, default 5)#top_n:N(1–20, default 5)#min_personas:N/#max_personas:N(2–10, default 4 / 6)
Hard Rules:
- Alle Persona/Synthese-Calls sind read-only — kein Tool darf Dateien im CWD modifizieren ausser dem finalen Report.
- Persona-Failures (eine Persona crashed) sind non-fatal — Tool macht mit Rest weiter, markiert Failure im Trace.
- Empty-Topic (alle Tags entfernt → leerer String) wird VOR dem ersten LLM-Call abgefangen.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 51 lines · 53 tokens per session scan A 191743c4f6dc
brainstorm is a skill published in the GitHub repository swDomass/AI_orchestrator (5 stars, last pushed 13d ago), licensed MIT. It adds 53 tokens to every session and 859 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
brainstorm
Structured creativity methods for idea generation: SCAMPER, Six Thinking Hats, Mind Mapping, Reverse Brainstorming, TRIZ, and Rapid Ideation.
ocx
Operate opencodex (ocx): discover CLI tasks offline, inspect local configuration, and manage a running proxy’s account pool, providers, models, routing, usage report, and management API. Use for proxy operation rather than editing the opencodex codebase.
free-llm-apis
Guide users through obtaining and configuring free API keys for LLM providers. Use when the user wants to set up a free LLM API, get a free API key, connect to a free model provider, configure an OpenAI-compatible endpoint at no cost, or asks about free tiers for AI models. Triggers on "free API key", "free LLM", "set…
llmwiki
Build and use a persistent, citation-traceable knowledge wiki from documents, research papers, notes, or project documentation. Use for llmwiki projects, retrieving reusable evidence for an agent task, or compiling a corpus for repeated questions. A one-off file read or live web search does not need a wiki.
content-angle-ranker
Rank content angles by engagement data, competition level, and platform fit. Data-driven angle selection instead of guesswork. Use this skill when the user has a keyword or product and needs to decide WHAT to create, which angle to take, which format to use, or which platform to target. Triggers on: "what angle should…
stock-eval
Evaluate US stocks with comprehensive fundamental and valuation analysis.